Description of multimorbidity clusters of admitted patients in medical departments of a general hospital

Matesanz-Fernández, María; Seoane-Pillado, Teresa; Íñiguez-Vázquez, Iria; Suárez-Gil, Roi; Pértega-Díaz, Sonia; Casariego-Vales, Emilio

doi:10.1136/postgradmedj-2020-139361

Cited by 10 publications

(8 citation statements)

References 42 publications

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“…A broad set studies detected a stronger association of mental and musculoskeletal multimorbidity with female sex, including neurological diseases ( 64 , 130 ), musculoskeletal and osteoarticular ( 42 , 64 , 67 , 71 , 93 , 102 , 126 , 130 , 131 ); and common mental disorders ( 42 , 132 ), like anxiety ( 44 , 67 , 86 , 93 , 114 ) depression ( 43 , 67 , 86 , 93 , 114 , 119 ), dementia ( 85 ) and emotional disorders ( 47 ). While cardiometabolic patterns ( 53 , 71 , 73 , 78 , 82 , 90 , 94 , 114 , 123 ), musculoskeletal ( 53 , 96 ), digestive and genitourinary patterns ( 99 , 110 , 124 , 131 ) were more frequent in men.…”

Section: Resultsmentioning

confidence: 99%

Social determinants of multimorbidity patterns: A systematic review

Álvarez‐Gálvez

Ortega-Martín

Carretero-Bravo

et al. 2023

Front. Public Health

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Social determinants of multimorbidity are poorly understood in clinical practice. This review aims to characterize the different multimorbidity patterns described in the literature while identifying the social and behavioral determinants that may affect their emergence and subsequent evolution. We searched PubMed, Embase, Scopus, Web of Science, Ovid MEDLINE, CINAHL Complete, PsycINFO and Google Scholar. In total, 97 studies were chosen from the 48,044 identified. Cardiometabolic, musculoskeletal, mental, and respiratory patterns were the most prevalent. Cardiometabolic multimorbidity profiles were common among men with low socioeconomic status, while musculoskeletal, mental and complex patterns were found to be more prevalent among women. Alcohol consumption and smoking increased the risk of multimorbidity, especially in men. While the association of multimorbidity with lower socioeconomic status is evident, patterns of mild multimorbidity, mental and respiratory related to middle and high socioeconomic status are also observed. The findings of the present review point to the need for further studies addressing the impact of multimorbidity and its social determinants in population groups where this problem remains invisible (e.g., women, children, adolescents and young adults, ethnic groups, disabled population, older people living alone and/or with few social relations), as well as further work with more heterogeneous samples (i.e., not only focusing on older people) and using more robust methodologies for better classification and subsequent understanding of multimorbidity patterns. Besides, more studies focusing on the social determinants of multimorbidity and its inequalities are urgently needed in low- and middle-income countries, where this problem is currently understudied.

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Section: Resultsmentioning

confidence: 99%

Social determinants of multimorbidity patterns: A systematic review

Álvarez‐Gálvez

Ortega-Martín

Carretero-Bravo

et al. 2023

Front. Public Health

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“…Latent network burdens related to arthritis and coronary heart disease have also been identified that share comorbid dimensions with asthma and respiratory disease, suggesting that there may be an underlying connection between these conditions and their relationship with depression. In fact, it has been reported in another study of 74220 hospitalized patients in Spain that such characteristics cluster in a community of chronic comorbidities [ 47 ]. Another investigation that included adults with mental disorders (e.g., depression) reported a comorbidity group with a higher prevalence of heart disease, respiratory disease, arthritis, kidney disease, and hypertension [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System

Ramos-Vera

Serpa

Saldarriaga

et al. 2023

Depression Research and Treatment

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Background. People with depression are at increased risk for comorbidities; however, the clustering of comorbidity patterns in these patients is still unclear. Objective. The aim of the study was to identify latent comorbidity patterns and explore the comorbidity network structure that included 12 chronic conditions in adults diagnosed with depressive disorder. Methods. A cross-sectional study was conducted based on secondary data from the 2017 behavioral risk factor surveillance system (BRFSS) covering all 50 American states. A sample of 89,209 U.S. participants, 29,079 men and 60,063 women aged 18 years or older, was considered using exploratory graphical analysis (EGA), a statistical graphical model that includes algorithms for grouping and factoring variables in a multivariate system of network relationships. Results. The EGA findings show that the network presents 3 latent comorbidity patterns, i.e., that comorbidities are grouped into 3 factors. The first group was composed of 7 comorbidities (obesity, cancer, high blood pressure, high blood cholesterol, arthritis, kidney disease, and diabetes). The second pattern of latent comorbidity included the diagnosis of asthma and respiratory diseases. The last factor grouped 3 conditions (heart attack, coronary heart disease, and stroke). Hypertension reported higher measures of network centrality. Conclusion. Associations between chronic conditions were reported; furthermore, they were grouped into 3 latent dimensions of comorbidity and reported network factor loadings. The implementation of care and treatment guidelines and protocols for patients with depressive symptomatology and multimorbidity is suggested.

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“…[ 29 ] A study from European countries found the most common health condition as hypertension which is similar to the present study. [ 23 30 ]…”

Section: Discussionmentioning

confidence: 99%

Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal

Burman

Sembiah²,

Dasgupta³

et al. 2022

Journal of Family Medicine and Primary Care

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Context: Multimorbidity is considered as a priority for global health research. It is defined as the coexistence of two or more chronic health conditions in an individual. It is increasingly being recognized as a major concern for primary care physicians due to its huge impact on individual, family, and societal level. Aim: The aim of this study was to find the quantum of gender-related inequalities and determinants of multimorbidity among the elderly people in a rural part of West Bengal. Materials and Methods: This is a cross-sectional study carried out among 246 elderly people (60 years and above) in a community setting from Oct 2017 to Sep 2018. Logistic regression analysis was done to find out the predictors of multimorbidity. Data were analyzed using the SPSS software (version 16.0. Chicago, SPSS Inc.). Results: Approximately 82% of the study subjects were suffering from multi-morbidity with a significant difference between males (80.9%) and females (88.5%). In binary logistics, people of both the genders aged >70 years, who had less than primary level education, had more than three children, whose source of income was from their children (sons/daughters), were dependent on others for daily routine were at high risk of being multimorbid; whereas depression was a significant predictor of multimorbidity in females and not in males. In multivariable analysis, age remained the only significant predictor for both the gender and for females; depression remained significant after adjusting with significant variables in binary logistics. Conclusion: Morbidity screening at each visit, individual as well as family counseling and lifestyle modifications help to cope with the rising burden of multimorbidity at the primary care level. More insight into the epidemiology of multi-morbidity is necessary to take steps to prevent it, lower its burden and align health-care services as per needs.

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Description of multimorbidity clusters of admitted patients in medical departments of a general hospital

Cited by 10 publications

References 42 publications

Social determinants of multimorbidity patterns: A systematic review

Social determinants of multimorbidity patterns: A systematic review

Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System

Gender inequalities in prevalence, pattern and predictors of multimorbidity among geriatric population in rural West Bengal

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